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Patch | Devices | E2E duration (s) | Fragment Query duration (s) | Service duration (s) | Object Size (MB) | Object Size #Fragments | Graph |
---|---|---|---|---|---|---|---|
1) Baseline | 1,000 | 11.8 | <0.1 * | 11.74012 | 0.3 | 86,000 | |
2,000 | 28.5 | <0.1 * | 28.401 | 0.7 | 172,000 | ||
5,000 | 87.0 | <0.1 * | 86.814 | 1,7 | 430,000 | ||
10,000 | 201.0 | <0.1* | 201.008 | 3.3 | 860,000 | ||
2) | 1,000 | 0.5 | 0.2 | 0.3 | 0.3 | 86,000 | |
2,000 | 1.0 | 0.4 | 0.6 | 0.7 | 172,000 | ||
5,000 | 2.5 | 1.1 | 1.4 | 1.7 | 430,000 | ||
10,000 | 7.0 | 2.9 | 4.0 | 3.3 | 860,000 | ||
1,000 | 3.0 | 1.3 | 1.7 | 0.3 | 86,000 | ||
2,000 | 5.5 | 2.3 | 3.2 | 0.7 | 172,000 | ||
5,000 | 11.0 | 5.4 | 5.6 | 1.7 | 430,000 | ||
10,000 | 25.4 | 11.7 | 13.6 | 3.3 | 860,000 |
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Query: cps/api/v1/dataspaces/openroadm/anchors/owb-msa221-anchor/node?xpath=/openroadm-devices/openroadm-device[@device-id='C201-7-13A-5A1']&include-descendants=true
Patch
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: https://gerrit.onap.org/r/c/cps/+/133511/12
Threads | E2E duration (s) | Succes Ratio | Fragment Query duration (s) |
---|---|---|---|
1 | 0.082 | 100% | 0.2 |
2 | 0.091 | 100% | 0.1 |
3 | 0.120 | 100% | 0.1 |
5 | 0.3 | 100% | 0.2 |
10 | 0.3 | 99.9% | 0.3 |
20 | 0.5 | 99.5% | 0.5 |
50 | 1.0 | 99.4% | 1.0 |
100 | 2.3 | 99.7% | 2.3 |
200 | 7.6 | 99.7% | 6.2 |
500 | 17.1 | 41.4% | 13.8 |
1,000 | 15.3 (many connection errors) | 26.0% | 11.9 |
Graphs:
- Average E2E Execution Time
- Internal Method Counts (total)
Observations
- From 10 Parallel request (of 10 sequential request) the client can't always connect and we see time out error (succes ratio <100%)
- Sequential request are fired faster than actual responses so from DB perspective they are almost parallel request as well
- Database probably already become bottleneck with 2 threads, effectively firening a total of 20 call very quickly. Its know that the DB connection pool/internal will slow down from 12 or more 'parallel' request
Graphs:
- Average E2E Execution Time
- Internal Method Counts (total)
Observations:
Data sheets
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